Performance Analysis for ROUGE And F-Measure in Arabic Text Summarization
Keywords:Arabic Language, text summarization, ROUGE, F-measure, preprocessing
Summarizing a document has become a necessity as, because so much information is produced every day. Document summary makes it simpler to understand the text document than it would be to read through a collection of documents. A foundation for creating an condensed version of one or more text documents is provided by text summary. It is a crucial method for finding pertinent information on the Internet or in sizable text libraries. Additionally, it is essential to extract data in a way that the user would find the information interesting. Extractive summarization and abstract summarization are the two basic approaches used for text summarizing. In order to create the summary, the extractive summarization method chooses the sentences from a Word document and arranges them according to their weight. Abstractive summarizing is a technique that takes the key ideas from a document's content and expresses them abstractly in plain English. Numerous summary methods have been created on the foundation of these two approaches. There are numerous techniques that are language-specific exclusively. In this paper, we used extractive summarization methods and got good results.
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